Amplifying existing knowledge, while maintaining validity, is fundamental to human reasoning, decision making, and the advancement of science. No matter how many rules a conventional expert system has, there will always be knowledge that is not contained by its knowledge base. As a practical matter, the allowable size of a knowledge base is relatively small. Segmenting the knowledge base helps, but it can still grow to be of unmanageable size. A need exists for a system and corresponding methodology that provides for capturing and amplifying existing knowledge while not requiring excessive data storage space.